WO2018103314A1 - 一种拍照方法、装置、终端及存储介质 - Google Patents

一种拍照方法、装置、终端及存储介质 Download PDF

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Publication number
WO2018103314A1
WO2018103314A1 PCT/CN2017/090945 CN2017090945W WO2018103314A1 WO 2018103314 A1 WO2018103314 A1 WO 2018103314A1 CN 2017090945 W CN2017090945 W CN 2017090945W WO 2018103314 A1 WO2018103314 A1 WO 2018103314A1
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Prior art keywords
image
evaluation value
parameter
value
quality evaluation
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English (en)
French (fr)
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纪德威
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ZTE Corp
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ZTE Corp
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Priority to US16/467,932 priority patent/US10939035B2/en
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N17/00—Diagnosis, testing or measuring for television systems or their details
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/0002—Inspection of images, e.g. flaw detection
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/40—Extraction of image or video features
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/98—Detection or correction of errors, e.g. by rescanning the pattern or by human intervention; Evaluation of the quality of the acquired patterns
    • G06V10/993—Evaluation of the quality of the acquired pattern
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
    • H04N23/60—Control of cameras or camera modules
    • H04N23/64—Computer-aided capture of images, e.g. transfer from script file into camera, check of taken image quality, advice or proposal for image composition or decision on when to take image
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
    • H04N23/60—Control of cameras or camera modules
    • H04N23/66—Remote control of cameras or camera parts, e.g. by remote control devices
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/20—Special algorithmic details
    • G06T2207/20021—Dividing image into blocks, subimages or windows
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30168—Image quality inspection
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
    • H04N23/60—Control of cameras or camera modules
    • H04N23/63—Control of cameras or camera modules by using electronic viewfinders
    • H04N23/631—Graphical user interfaces [GUI] specially adapted for controlling image capture or setting capture parameters
    • H04N23/632—Graphical user interfaces [GUI] specially adapted for controlling image capture or setting capture parameters for displaying or modifying preview images prior to image capturing, e.g. variety of image resolutions or capturing parameters

Definitions

  • the present disclosure relates to the field of terminal application technologies, and in particular, to a photographing method, device, terminal, and storage medium.
  • the photographing method, device, terminal and storage medium provided by the embodiments of the present disclosure achieve effective capture of the target scene, thereby ensuring the quality of the image captured by the terminal.
  • an embodiment of the present disclosure provides a photographing method, the method comprising:
  • Acquiring an image for the image acquisition area acquiring an image quality evaluation value of the image, the image quality evaluation value being used to characterize the quality of the image;
  • a photographing instruction is generated, the photographing instruction is executed, the image is used as a target image, and the target image is saved.
  • the obtaining an image quality evaluation value of the image includes:
  • the attribute parameters include at least one of the following attribute parameters: sharpness, contrast, saturation, brightness, and noise.
  • determining the image quality evaluation value of the image according to the parameter value of the attribute parameter includes:
  • An evaluation value of the attribute parameter is determined according to a parameter value of an attribute parameter of the image; and an image quality evaluation value of the image is determined according to the evaluation value of the attribute parameter.
  • the method further includes:
  • the image quality evaluation value of the image is greater than a preset evaluation value threshold, it is determined that the image quality evaluation value of the image satisfies a preset quality condition.
  • the method further includes:
  • the image quality evaluation value of the image When the image quality evaluation value of the image does not satisfy the preset quality condition, the image quality evaluation value of the image is adjusted according to the parameter value of the attribute parameter.
  • the image quality evaluation value of the image according to the parameter value of the attribute parameter Making adjustments includes:
  • the parameter values of the respective phase parameters are adjusted according to the sorting result to adjust the image quality evaluation value of the image.
  • an embodiment of the present disclosure further provides a photographing method, the method comprising:
  • the photographing instruction is executed to save the target image.
  • the acquiring an image quality evaluation value of each of the at least one image includes:
  • an image quality evaluation value of each image is calculated according to parameter values of the at least one attribute parameter of each image.
  • the calculating the image quality evaluation value of each image according to the parameter value of the at least one attribute parameter of each image includes:
  • the image is divided into at least two image blocks according to a preset partitioning strategy
  • An evaluation value of the attribute parameter is determined according to a parameter value of an attribute parameter of the image; and an image quality evaluation value of the image is determined according to the evaluation value of the attribute parameter.
  • the method further includes:
  • An image whose image quality evaluation value of the image is larger than a preset evaluation value threshold is determined as an image satisfying a preset quality condition.
  • the method further includes:
  • an image with the largest image quality evaluation value in the at least one image is used as the adjustment target image
  • adjusting the quality evaluation value of the adjustment target image according to the parameter value of the at least one attribute parameter of the adjustment target image includes:
  • adjusting the quality evaluation value of the adjustment target image includes:
  • the parameter values of the sorted second target attribute parameters are sequentially adjusted until the image quality evaluation value of the adjustment target image is greater than or equal to the preset evaluation value threshold.
  • the attribute parameters include: sharpness, contrast, saturation, brightness, and noise.
  • An embodiment of the present disclosure further provides a photographing apparatus, where the apparatus includes:
  • An acquisition module configured to acquire at least one image acquired for the same image acquisition area
  • a processing module configured to acquire an image quality evaluation value of each of the at least one image, the image quality evaluation value being used to characterize a quality of each of the images;
  • a determining module configured to determine an image in which the image quality evaluation value in the at least one image satisfies a preset quality condition as a target image, and generate a photographing instruction
  • the apparatus further includes: an adjustment module, configured to sort the at least one image according to the image quality evaluation value when an image quality evaluation value of each image does not satisfy a preset quality condition And determining, as the adjustment target image, an image having the largest image quality evaluation value in the at least one image; and adjusting a quality evaluation value of the adjustment target image according to the parameter value of the at least one attribute parameter of the adjustment target image.
  • an adjustment module configured to sort the at least one image according to the image quality evaluation value when an image quality evaluation value of each image does not satisfy a preset quality condition And determining, as the adjustment target image, an image having the largest image quality evaluation value in the at least one image; and adjusting a quality evaluation value of the adjustment target image according to the parameter value of the at least one attribute parameter of the adjustment target image.
  • the embodiment of the present disclosure further provides a terminal, including: an image sensor, a processor, and a memory; wherein
  • the image sensor is configured to acquire at least one image acquired for the same image acquisition area
  • the processor configured to acquire an image quality evaluation value of each of the at least one image, the image quality evaluation value being used to characterize a quality of each of the images; An image whose image quality evaluation value satisfies a preset quality condition is determined as a target image, and a photographing instruction is generated; and the photographing instruction is executed to save the target image in the memory.
  • Embodiments of the present disclosure also provide a storage medium including a stored program that executes the above-described photographing method while the program is running.
  • the photographing method, device, terminal and storage medium of the embodiment of the present disclosure acquires an image for an image acquisition area, and acquires an image quality evaluation value of the image, where the image quality evaluation value is used to represent the quality of the image;
  • the image quality evaluation value satisfies the preset quality condition
  • the image of the image acquisition area is a plurality of images
  • the image with the image quality evaluation value satisfying the preset quality condition is taken as the result of the photographing, thereby realizing the effective capture of the target scene, thereby ensuring the quality of the photographed by the terminal.
  • FIG. 1-1 is a schematic flowchart of a photographing method in Embodiment 1 of the present disclosure
  • FIG. 1-2 is a schematic flowchart of a photographing method in Embodiment 2 of the present disclosure
  • FIG. 2 is a schematic flowchart of a photographing method in Embodiment 3 of the present disclosure
  • FIG. 3 is a schematic flowchart of a photographing method in Embodiment 4 of the present disclosure.
  • Embodiment 4 is a schematic flow chart of a saturation analysis method in Embodiment 4 of the present disclosure.
  • FIG. 5 is a schematic structural diagram of a photographing apparatus according to Embodiment 5 of the present disclosure.
  • FIG. 6 is another schematic structural diagram of a photographing apparatus according to Embodiment 5 of the present disclosure.
  • FIG. 7 is a schematic structural diagram of a terminal in Embodiment 6 of the present disclosure.
  • Embodiment 1 is a diagrammatic representation of Embodiment 1:
  • the line main body may be a photographing device, and the photographing device may be built in or externally connected to a terminal.
  • the terminal can be a smartphone, a tablet, a digital camera, or the like.
  • FIG. 1-1 is a schematic flowchart of a photographing method in the first embodiment of the present disclosure. Referring to FIG. 1-1, the method includes:
  • S1101 Acquire an image for an image acquisition area, and obtain an image quality evaluation value of the image, where the image quality evaluation value is used to represent the quality of the image;
  • the mode of photographing may be an automatic photographing mode or a manual photographing mode.
  • the automatic photographing mode when the terminal receives the automatic photographing instruction, the automatic photographing mode is entered. At this time, the image of the image capturing area is acquired by the camera.
  • the operation of triggering the automatic photographing instruction or the manual photographing instruction can be operated by voice/click. The triggering of the physical button/virtual button on the operation/touch operation terminal enters the corresponding photographing mode.
  • the image is analyzed to obtain an image quality evaluation value of the image
  • the acquiring the image quality evaluation value of the image includes: acquiring a parameter value of the attribute parameter of the image, according to the The parameter value of the attribute parameter determines an image quality evaluation value of the image; the attribute parameter includes at least one of the following attribute parameters: sharpness, contrast, saturation, brightness, and noise.
  • the method of obtaining the attribute parameters of the image may adopt a feature extraction method, such as: Fourier transform, window Fourier transform, wavelet change, least squares method, boundary direction histogram, texture feature extraction based on Tzmura texture feature, etc. There may be other algorithms, which are not limited in the embodiments of the present disclosure.
  • Determining, according to the parameter value of the attribute parameter, the image quality evaluation value of the image comprises: dividing the image into at least two image blocks according to a preset partitioning strategy; calculating each of the at least two image blocks a parameter value of an attribute parameter of an image block; determining a parameter value of the attribute parameter of the image block according to the parameter value of the attribute parameter of each image block; determining the parameter according to the parameter value of the attribute parameter of the image An evaluation value of the attribute parameter is determined; an image quality evaluation value of the image is determined according to the evaluation value of the attribute parameter.
  • a feasible implementation manner of determining a parameter value of an attribute parameter of an image block is: selecting a geometric center point of the image block, calculating a parameter value of an attribute parameter of a geometric center point of the image block, and The parameter value of the attribute parameter at the geometric center of the image block as the image
  • the parameter value of the attribute parameter of the block; the parameter value of the attribute parameter of the image is a value range of the same attribute parameter of all image blocks, for example, a parameter value for calculating the saturation of the image is used as an example: the image is selected The geometric center point of the block, the parameter value of the saturation of the geometric center point is calculated, and the saturation value of the geometric center point is used as the parameter value of the saturation of the corresponding block, and the parameter value of the saturation of the image is The range of values in the saturation of the image.
  • the preset partitioning policy is a default or user-defined strategy of dividing an image into at least two image blocks according to a preset length and width. After the image is divided into at least two image blocks and the parameter values of the attribute parameters of each image block are obtained, the parameter values of the attribute parameters of the image are determined, and the image quality of each image is calculated according to the parameter values of the attribute parameters of the image. The assessed value.
  • the manner of calculating the image quality evaluation value of each image according to the parameter value of the attribute parameter of the image may be, but is not limited to, the following implementation manner: mapping relationship between the parameter value and the evaluation value according to the preset attribute parameter Determining an evaluation value of an attribute parameter of each image, and determining an image quality evaluation value of the image based on the evaluation value of the attribute parameter.
  • the value of the saturation of the image is determined according to the value of the saturation of each image block, and further, the saturation of the image is The evaluation value corresponding to the value is determined as the image quality evaluation value of the image.
  • the attribute parameter of each image block is a plurality of attribute parameters such as saturation, contrast, the saturation and contrast of the image are determined according to the saturation and contrast of each image block, and according to the parameters of saturation and contrast respectively.
  • the value determines the evaluation value corresponding to the saturation and the contrast, and calculates the image quality evaluation value by using the saturation degree system and the contrast corresponding evaluation value by a preset calculation method.
  • the preset calculation method may be calculating the attribute parameter.
  • the arithmetic mean value of the evaluation value and the like are calculated, and the embodiment of the present disclosure does not limit this.
  • the parameter value of the attribute parameter of the image may be an interval value, and according to the mapping relationship between the parameter value of the preset attribute parameter and the evaluation value of the attribute parameter, searching for a mapping interval to which the parameter value of the attribute parameter of the image belongs, thereby Determining an evaluation value of an attribute parameter of the image; determining the image quality evaluation value is quantized by an arithmetic mean value of the evaluation value of at least one attribute parameter of the image, for example, taking saturation and contrast as an example to calculate an image quality evaluation of the image
  • the value is as follows: according to the mapping relationship between the preset saturation parameter value and the saturation evaluation value, the evaluation value of the saturation of each image is obtained; the parameter value and the contrast evaluation value according to the preset contrast ratio The mapping relationship between the two is obtained, and an evaluation value of the contrast of each image is obtained, an arithmetic mean value of the evaluation value of the saturation of each one and the evaluation value of the contrast is calculated, and the arithmetic mean value is taken as the image quality evaluation value of the corresponding image
  • S1102 Determine that the image quality evaluation value satisfies a preset quality condition, generate a photographing instruction, execute the photographing instruction, and use the image as a target image to save the target image.
  • the evaluation value threshold may be set by the system by default, or may be customized for the user at any time during the triggering of the photographing process; a feasible implementation manner of the user preset evaluation value threshold is: prompting the user to set the trigger through the screen The threshold of the image quality evaluation value for automatic photographing.
  • the image quality evaluation value of the image When the image quality evaluation value of the image does not satisfy the preset quality condition, the image quality evaluation value of the image is adjusted according to the parameter value of the attribute parameter.
  • the parameter value of the genus parameter may be directly adjusted, so that the image quality evaluation value can be greater than a preset evaluation value threshold to adjust the image quality of the image. So that the saved target image is an image that satisfies the quality condition.
  • the adjusting the image quality evaluation value of the image according to the parameter value of the attribute parameter includes:
  • the parameter value of the attribute parameter is adjusted according to the size of the evaluation value of the attribute parameter, for example, the attribute parameter with a large evaluation value is preferentially adjusted to Improve the overall image quality evaluation value of the image.
  • the photographing instruction is generated to save the image;
  • the quality condition the quality of the image is adjusted to ensure that the saved image is an image that satisfies the quality condition.
  • the image is divided into a plurality of image blocks, so that the parameter values of the image phase parameters are determined according to the parameter values of the attribute parameters of the image blocks, thereby determining the image of the image.
  • the quality evaluation value is used to accurately calculate the image quality evaluation value of the image.
  • An optional embodiment of the present disclosure provides a photographing method.
  • the execution body of the photographing method of the alternative embodiment of the present disclosure may be a photographing device, and the photographing device may be built in or externally connected to a terminal.
  • the terminal can be a smartphone, a tablet, a digital camera, or the like.
  • FIG. 1-2 is a schematic flowchart of a photographing method in an alternative embodiment 2 of the present disclosure. Referring to FIG. 1-2, the method includes:
  • S101 Acquire at least one image collected for the same image acquisition area
  • the terminal collects the same image acquisition area through the image sensor. At least one image; here, at least one of the acquired images is cached as a selected image of the target image, and is not used as the final saved target image.
  • the image acquisition area refers to the framing area of the image sensor. The number of images collected can be customized by the user according to actual needs, or can be set by the system by default. Of course, there may be other setting manners, which are not limited in the embodiment of the present disclosure.
  • S102 Acquire an image quality evaluation value of each of the at least one image, where the image quality evaluation value is used to represent the quality of each image;
  • the terminal needs to analyze the collected currently cached image to obtain an image quality evaluation value of each image
  • the image quality evaluation value of the image may be an arithmetic mean of the evaluation values of at least one attribute parameter of the image; the method of extracting the attribute parameter of the image may adopt feature extraction Methods, such as: Fourier transform, window Fourier transform, wavelet variation, least squares method, boundary direction histogram, texture feature extraction based on Tzmura texture features, etc., of course, there may be other algorithms, embodiments of the present disclosure Not limited.
  • the acquiring an image quality evaluation value of each of the at least one image includes: acquiring a parameter value of at least one attribute parameter of each of the images According to a preset rule, an image quality evaluation value of each image is calculated according to parameter values of at least one attribute parameter of each image.
  • the attribute parameters of the image may be contrast, saturation, brightness, sharpness, noise, etc., which are not limited by the embodiments of the present disclosure; the parameter values of these attribute parameters may be used as an evaluation index for measuring the image quality of the image.
  • Calculating an image quality evaluation value of each image according to the parameter value of the at least one attribute parameter of each image including: dividing, for each image, the image into at least two image regions according to a preset partitioning strategy a parameter; calculating a parameter value of at least one attribute parameter of each of the at least two image blocks; determining an attribute parameter of the image block according to a parameter value of an attribute parameter of each of the image blocks a parameter value; determining an evaluation value of the attribute parameter according to a parameter value of an attribute parameter of the image; and determining an image quality evaluation value of the image according to the evaluation value of the attribute parameter.
  • a feasible implementation manner of determining a parameter value of an attribute parameter of an image block is: selecting a geometric center point of the image block, calculating a parameter value of an attribute parameter of a geometric center point of the image block, and The parameter value of the attribute parameter at the geometric center of the image block is used as the parameter value of the attribute parameter of the image block; the parameter value of the attribute parameter of the image is the value range of the same attribute parameter of all image blocks, for example, to calculate
  • the parameter value of the saturation of the image is described as an example: the geometric center point of the image block is selected, the parameter value of the saturation of the geometric center point is calculated, and the saturation value of the geometric center point is taken as the saturation of the corresponding block.
  • the parameter value of the degree, the parameter value of the saturation of the image is the value range of the saturation in the image.
  • the preset partitioning strategy is a default or user-defined image divided into at least two image blocks according to a preset length and width.
  • the step of calculating the image quality evaluation value of each image according to the parameter value of the at least one attribute parameter may be, but not limited to, the following one
  • the current mode is: determining an evaluation value of at least one attribute parameter of each image according to a mapping relationship between a parameter value of the preset attribute parameter and the evaluation value, and calculating an arithmetic mean of the evaluation value of at least one attribute parameter of each image. Value, the arithmetic mean of each image is taken as the image quality evaluation value of the corresponding image.
  • the mapping interval to which the parameter value of the attribute parameter of the image belongs is determined, thereby determining The evaluation value of the attribute parameter of the image; the determination of the image quality evaluation value is determined by the arithmetic mean value of the evaluation value of the at least one attribute parameter of the image, for example, taking the saturation and contrast as an example, calculating the image quality evaluation value of the image
  • the mapping relationship between the preset saturation parameter value and the saturation evaluation value the evaluation value of the saturation of each image is obtained; according to the preset contrast value and the contrast evaluation value
  • the mapping relationship is obtained, an evaluation value of the contrast of each image is obtained, an arithmetic mean value of the evaluation value of the saturation of each one and the evaluation value of the contrast is calculated, and the arithmetic mean value is taken as the image quality evaluation value of the corresponding image.
  • the evaluation value of the attribute parameter of the image may be directly used as the image quality evaluation value of the image.
  • S103 Determine an image that satisfies a preset quality condition in the image quality evaluation value in the at least one image as a target image, and generate a photographing instruction;
  • the image quality evaluation value of each of the at least one image is compared with a preset evaluation value threshold; and an image whose image quality evaluation value of the image is greater than a preset evaluation value threshold is determined to satisfy the preset Image of quality conditions.
  • the preset evaluation value threshold may be set by the system by default, or may be customized for the user at any time during the triggering of the photographing process; a feasible implementation manner for the user to preset the preset evaluation value threshold is: The screen prompts the user to set a threshold for the image quality evaluation value that triggers the automatic photographing.
  • the target image After the target image is directly saved, the target image can be displayed through the screen of the terminal.
  • the image whose image quality evaluation value does not satisfy the preset quality condition can be deleted.
  • the foregoing process may be: when the terminal uses the image acquisition module to separately framing the same scene, after acquiring at least one image at a time, processing each image; or using the image acquisition module for the same scene.
  • framing separately after an image is acquired, the image is processed immediately until the i image quality satisfies the quality condition required by the preset shooting, and the automatic photographing is triggered, where i is a positive integer greater than or equal to 1.
  • the embodiment of the present disclosure acquires at least one image by using the same image acquisition area; first, processing each image of the at least one image to obtain an image quality evaluation value of each image, and the image quality evaluation value is used for Characterizing the quality of each image; performing image quality evaluation on images acquired for the same acquisition area before automatically triggering the photograph, and then determining an image of the image quality evaluation value of at least one image greater than or equal to the preset evaluation value threshold as the target And generating a photographing instruction; executing a photographing instruction, saving the target image, and deleting an image of the image quality evaluation value of the at least one image that is smaller than a preset evaluation value threshold; if the image quality evaluation value of the image is greater than or equal to automatically triggering the photographing Threshold value, automatic triggering of the photo, can automatically trigger the photo, avoiding the inability to capture the target scene in time, and ensuring the quality of the photograph taken.
  • Embodiment 3 is a diagrammatic representation of Embodiment 3
  • An embodiment of the present disclosure provides a photographing method. As shown in FIG. 2, in the embodiment of the present disclosure, a description is given for a case where each of at least one image does not satisfy a preset quality condition:
  • the adjustment of the parameter value of the attribute parameter of the image may be performed on the kth image in the at least one image.
  • the adjustment of the image quality evaluation value may also be an adjustment of the image quality evaluation value of the n images in the at least one image; the embodiment of the present disclosure performs the image quality evaluation value of the kth image in the at least one image.
  • S201 collecting at least one image for the same image acquisition area
  • S202 Acquire an image quality evaluation value of each of the at least one image, where the image quality evaluation value is used to represent the quality of each of the images;
  • the adjustment of the quality evaluation value can be adjusted by adjusting the attribute parameters affecting the image quality, and the adjustment method can adopt linear correction and nonlinear correction.
  • the feasible implementation manner of S203 can be implemented in the following two ways:
  • the value of the first preset threshold may be the same as the value of the preset evaluation value threshold, or may be different from the value of the preset evaluation value threshold, which is not limited by the embodiment of the present disclosure
  • the parameter value of the target attribute parameter may be a parameter value of each attribute parameter in the first target attribute parameter, for example, processing the adjustment target image to obtain a parameter value of the contrast of the adjustment target image respectively (a, b)
  • the parameter value of the brightness is (c, d), and the parameter value of the saturation value is (e, f); according to the mapping relationship between the parameter value of the preset contrast and the evaluation value, the evaluation value of the contrast is 60;
  • the evaluation value of the brightness can be obtained as 70; according to the mapping relationship between the parameter value of the preset saturation and the evaluation value, the saturation can be evaluated.
  • the value is 80; since the first preset threshold is 75, the attribute parameters less than 75 are contrast and brightness, and the parameter values of contrast and brightness are adjusted respectively until
  • the size of the first preset threshold may be the same as or different from the size of the second preset threshold.
  • the second target attribute parameter is sorted according to the size of the evaluation value, for example, it may be in the order of the evaluation value from small to large, and the embodiment of the present disclosure is not limited thereto.
  • the second target attribute parameter includes all the attribute parameters. Sort the evaluation values of all attribute parameters.
  • the step of sequentially adjusting the parameter values of the adjusted second target attribute parameter may be not limited to the following implementation manner: first adjusting the first attribute parameter of the second target attribute parameter, and calculating the adjusted adjustment target
  • the image quality evaluation value of the image if the adjusted image quality evaluation value of the adjustment target image is greater than or equal to the preset evaluation value threshold, the adjustment target image is saved; if the adjusted image quality evaluation value of the adjustment target image is smaller than the preset The evaluation value threshold is adjusted, and the second attribute parameter is adjusted until the image quality evaluation value of the kth image is greater than a preset evaluation value threshold.
  • the adjustment target image is processed to obtain a parameter value for adjusting the contrast of the target image.
  • the parameter value of the brightness is (c, d), and the parameter value of the saturation is (e, f); the contrast is obtained according to the mapping relationship between the parameter value of the preset contrast and the evaluation value.
  • the evaluation value is 60; according to the mapping relationship between the parameter value of the preset brightness and the evaluation value, the evaluation value of the brightness is 70; according to the preset The relationship between the parameter value of the sum and the evaluation value, the evaluation value of the saturation is 80; since the second preset threshold is 75, the attribute parameters less than 75 are contrast and brightness, since the evaluation value of the contrast is smaller than
  • For the evaluation value of the brightness first adjust the parameter value of the contrast until the evaluation value of the contrast is 75, and then judge whether the arithmetic mean value of the adjusted value of the adjusted contrast, the evaluation value of the brightness, and the evaluation value of the saturation is greater than or equal to the preset value.
  • the evaluation value threshold is 75. Since the adjusted arithmetic mean is equal to the preset evaluation value threshold, the parameter value of the brightness is no
  • S204 Determine an image that satisfies a preset quality condition in the image quality evaluation value in the at least one image as a target image, and generate a photographing instruction;
  • the image that satisfies the preset quality condition is the adjusted adjustment target image.
  • the terminal adjusts the attribute parameter of the current preview image, so that the image quality evaluation value of the current preview image satisfies the preset quality condition, and then saves the adjusted current preview image to realize automatic photographing, and The quality of the photos taken is guaranteed.
  • Embodiment 4 is a diagrammatic representation of Embodiment 4:
  • the embodiment of the present disclosure provides a photographing method. As shown in FIG. 3, the implementation process of the embodiment of the present disclosure is described in detail:
  • S302 prompt the user whether the automatic photographing function needs to be turned on
  • the default threshold is adopted.
  • the threshold for photo capture is 90 points.
  • the image quality analysis includes the following aspects: 1. Saturation analysis; 2. Noise analysis; 3. Sharpness analysis; 4. Contrast analysis; 5. Luminance analysis.
  • Saturation analysis includes the following aspects: 1. Saturation analysis; 2. Noise analysis; 3. Sharpness analysis; 4. Contrast analysis; 5. Luminance analysis.
  • the analysis of other parameters may also be performed, and the embodiment of the present disclosure is not limited.
  • the saturation analysis is taken as an example for detailed description. Referring to FIG. 4, it is assumed that the width and height of the current preview picture are W and H, respectively.
  • the preview picture is divided into a1, a2, ... a(N-1), aN, a total of N blocks, and N is an integer greater than or equal to 1.
  • the center point of the i-th block in the N blocks is selected, and the saturation Si of the center point of the block is obtained according to the saturation calculation formula (1);
  • S is the saturation of the center point of the block
  • R is the value of the red channel at the center point of the block
  • G is the value of the green channel at the center point of the block
  • B is the value of the blue channel at the center point of the block.
  • the saturation range of the current preview picture is obtained as (Smin, Smax);
  • the saturation value ranges from (Smin, Smax) as the parameter value of the saturation.
  • the terminal can also obtain the parameter value of the noise, the parameter value of the sharpness, the parameter value of the contrast, and the parameter value of the brightness.
  • an evaluation value S_saturation of the parameter value (Smin, Smax) of the saturation obtained in S304 is obtained according to the mapping relationship between the parameter value of the preset saturation and the evaluation value of the saturation. For example, assuming (Smin, Smax) is between 85% and 95%, then based on the above mapping relationship, an evaluation value of saturation of 95 points can be obtained.
  • the terminal may further obtain an evaluation value S_contrast of the contrast of the current preview picture, an evaluation value S_luminance of the brightness, and a sharpness according to a mapping relationship between the parameter value of the preset attribute parameter and the evaluation value of the attribute parameter.
  • S306 Calculate an image quality evaluation value Score of the current preview picture according to S_saturation, S_contrast, S_luminance, S_sharpness, and S_noise;
  • the terminal can calculate the image quality evaluation value of the current preview picture according to the following formula (4).
  • S307 Compare the size of Score and S_threshold, when Score is greater than or equal to S_threshold, execute S313; when Score is less than S_threshold, execute S308;
  • S_threshold is the threshold for triggering a photo.
  • S308 Filtering attribute parameters smaller than S_threshold from S_saturation, S_contrast, S_luminance, S_sharpness, and S_noise;
  • the initial value of i is 5.
  • S311 calculating an image quality evaluation value Score_mod of the current preview image based on the parameter value of the adjusted attribute parameter;
  • Embodiment 5 is a diagrammatic representation of Embodiment 5:
  • the present embodiment provides a photographing apparatus that can be applied to the terminal described in one or more of the above embodiments.
  • the photographing apparatus 50 includes: an acquisition module 51 configured to acquire at least one image acquired for the same image acquisition area; and a processing module 52, configured to acquire an image quality evaluation value of each of the at least one image, the image quality evaluation value is used to represent the quality of each image; and the determining module 53 is configured to satisfy the image quality evaluation value in the at least one image.
  • the image of the preset quality condition is determined as the target image, and a photographing instruction is generated; the saving module 54 is configured to execute the photographing instruction and save the target image.
  • the processing module 52 acquires each of the at least one image An image quality evaluation value of an image, comprising: obtaining parameter values of at least one attribute parameter of each image; and calculating an image quality evaluation value of each image according to a parameter value of at least one attribute parameter of each image according to a preset rule .
  • the processing module 52 calculates an image quality evaluation value of each image according to the parameter value of the at least one attribute parameter of each image, and: according to each image, the image is preset according to each image.
  • the partitioning strategy is divided into at least two image blocks; calculating parameter values of at least one attribute parameter of each of the at least two image blocks; determining according to parameter values of the attribute parameters of each of the image blocks a parameter value of the attribute parameter of the image block; determining an evaluation value of the attribute parameter according to the parameter value of the attribute parameter of the image; and determining an image quality evaluation value of the image according to the evaluation value of the attribute parameter.
  • the photographing apparatus 50 may further include: a comparison module 55 configured to set an image quality evaluation value of each of the at least one image with a preset evaluation value. The threshold is compared; an image whose image quality evaluation value of the image is larger than a preset evaluation value threshold is determined as an image satisfying a preset quality condition.
  • a comparison module 55 configured to set an image quality evaluation value of each of the at least one image with a preset evaluation value. The threshold is compared; an image whose image quality evaluation value of the image is larger than a preset evaluation value threshold is determined as an image satisfying a preset quality condition.
  • the photographing apparatus may further include: an adjustment module 56 configured to set the at least one if an image quality evaluation value of each image does not satisfy a preset quality condition An image having the largest image quality evaluation value in the image is used as an adjustment target image; and a quality evaluation value of the adjustment target image is adjusted according to a parameter value of at least one attribute parameter of the adjustment target image.
  • the acquisition module, the processing module, the determining module, the saving module, the comparison module, and the adjustment module may all be provided by a central processing unit (CPU), a microprocessor (MPU, Microprocessor Unit), and a digital camera.
  • CPU central processing unit
  • MPU Microprocessor Unit
  • DSP Digital Signal Processing
  • FPGA Field-Programmable Gate Array
  • an embodiment of the present disclosure provides a terminal that is consistent with the terminal described in one or more of the foregoing embodiments.
  • the terminal 70 includes: an image sensor 71, a processor 72, and a memory 73, wherein the image sensor 71 is configured to acquire at least one image acquired for the same image acquisition area; 72.
  • Set an image quality evaluation value for acquiring each of the at least one image the image quality evaluation value is used to represent a quality of each of the images; and the image quality evaluation is performed in the at least one image
  • An image whose value satisfies a preset quality condition is determined as a target image, and a photographing instruction is generated; and the photographing instruction is executed to save the target image in the memory 73.
  • the above processor may be implemented by a CPU, an MPU, a DSP, an FPGA, or the like.
  • the embodiments of the present disclosure are not limited.
  • an embodiment of the present disclosure provides a storage medium.
  • the foregoing storage medium may be configured to store program code for performing the following steps:
  • S1 acquiring an image for an image acquisition area, acquiring an image quality evaluation value of the image, and the image quality evaluation value is used to represent the quality of the image;
  • the storage medium is further arranged to store program code for performing the following steps:
  • embodiments of the present disclosure can be provided as a method, system, or computer program product. Accordingly, the present disclosure may take the form of a hardware embodiment, a software embodiment, or a combination of software and hardware aspects. Moreover, the present disclosure may take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage and optical storage, etc.) including computer usable program code.
  • the computer program instructions can also be stored in a computer readable memory that can direct a computer or other programmable data processing device to operate in a particular manner, such that the instructions stored in the computer readable memory produce an article of manufacture comprising the instruction device.
  • the apparatus implements the functions specified in one or more blocks of a flow or a flow and/or block diagram of the flowchart.
  • These computer program instructions can also be loaded onto a computer or other programmable data processing device such that a series of operational steps are performed on a computer or other programmable device to produce computer-implemented processing for execution on a computer or other programmable device.
  • the instructions are provided for implementation in a block or blocks of a flow or a flow and/or a block diagram of the flowchart Functional steps.
  • an image for an image acquisition area acquiring an image quality evaluation value of the image, the image quality evaluation value is used to represent a quality of the image; and determining that the image quality evaluation value meets a preset a quality condition, generating a photographing instruction, executing the photographing instruction, using the image as a target image, and saving the target image, and thus, taking an image whose image quality evaluation value satisfies a preset quality condition as a result of photographing,
  • the image for the image acquisition area is a plurality of images
  • the image whose evaluation value of the image quality satisfies the preset quality condition is taken as the result of the photographing, thereby realizing the effective capture of the target scene, thereby ensuring the terminal.
  • the quality of the shot is a plurality of images.

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Abstract

本公开实施例公开了一种拍照方法，该方法包括：获取针对图像采集区域的图像，获取所述图像的图像质量评估值，所述图像质量评估值用于表征所述图像的质量；确定所述图像质量评估值满足预设的质量条件时，生成拍照指令，执行所述拍照指令，将所述图像作为目标图像，保存所述目标图像。本公开实施例同时公开了一种拍照的装置及终端。

Description

一种拍照方法、装置、终端及存储介质 技术领域
本公开涉及终端应用技术领域，尤其涉及一种拍照方法、装置、终端及存储介质。
背景技术
随着移动智能终端领域影像技术的快速发展，移动智能终端逐步取代了卡片机，成为人们日常生活中拍摄图片、视频的一种重要工具，与此同时，随着用户专业素养的不断提高，用户对移动终端的影像质量要求也越来越高，因此，随手拍出好照片也日益成为各大移动终端厂商所追求的一个目标。
在用户使用终端进行拍照的过程中，常常会碰到这种情况，即当遇到一些美妙的风景拿起手中的移动终端，再去按下快门时，往往这些美妙的风景转瞬即逝，难以捕捉；又或者捕捉下来的画面质量不是最佳的。
可见，相关技术不能实现对目标场景的有效抓拍。
发明内容
为解决相关技术中存在的技术问题，本公开实施例提供的拍照方法、装置、终端及存储介质，实现了对目标场景的有效抓拍，进而保证了终端所拍摄到的图像的质量。
为达到上述目的，本公开的技术方案是这样实现的：
一方面，本公开实施例提供了一种拍照方法，所述方法包括：
获取针对图像采集区域的图像，获取所述图像的图像质量评估值，所述图像质量评估值用于表征所述图像的质量；
确定所述图像质量评估值满足预设的质量条件时，生成拍照指令，执行所述拍照指令，将所述图像作为目标图像，保存所述目标图像。
在上述方案中，所述获取所述图像的图像质量评估值包括：
获取所述图像的属性参数的参数值，根据所述属性参数的参数值确定所述图像的图像质量评估值；
所述属性参数包括以下属性参数至少之一：锐度，对比度、饱和度、亮度和噪点。
在上述方案中，所述根据所述属性参数的参数值确定所述图像的图像质量评估值包括：
将所述图像按照预设分区策略划分为至少两个图像区块；
计算所述至少两个图像区块中每一个图像区块的属性参数的参数值；
根据所述每一个图像区块的属性参数的参数值确定所述图像区块的属性参数的参数值；
根据所述图像的属性参数的参数值确定所述属性参数的评估值；根据所述属性参数的评估值确定所述图像的图像质量评估值。
在上述方案中，所述方法还包括：
将所述图像的图像质量评估值与预设的评估值阈值进行比较；
当所述图像的图像质量评估值大于预设的评估值阈值时，确定所述图像的图像质量评估值满足预设的质量条件。
在上述方案中，所述方法还包括：
当所述图像的图像质量评估值不满足预设的质量条件时，根据所述属性参数的参数值对所述图像的图像质量评估值进行调整。
在上述方案中，当所述属性参数包括锐度，对比度、饱和度、亮度和噪点中的至少两个属性参数时，所述根据所述属性参数的参数值对所述图像的图像质量评估值进行调整包括：
确定所述每一个属性参数的参数值对应的评估值，根据所述评估值的大小对所述属性参数进行排序得到排序结果；
根据所述排序结果调整各属相参数的参数值以对所述图像的图像质量评估值进行调整。
一方面，本公开实施例还提供了一种拍照方法，所述方法包括：
获取针对同一图像采集区域采集的至少一个图像；
获取所述至少一个图像中的每一个图像的图像质量评估值，所述图像质量评估值用于表征所述每一个图像的质量；
将所述至少一个图像中所述图像质量评估值满足预设的质量条件的图像确定为目标图像，并生成拍照指令；
执行所述拍照指令，保存所述目标图像，。
在上述方案中，所述获取所述至少一个图像中的每一个图像的图像质量评估值，包括：
获取所述每一个图像的至少一个属性参数的参数值；
按照预设规则，根据每一个图像的所述至少一个属性参数的参数值，计算每一个图像的图像质量评估值。
在上述方案中，所述根据每一个图像的所述至少一个属性参数的参数值，计算每一个图像的图像质量评估值，包括：
针对每一个图像，将所述图像按照预设分区策略划分为至少两个图像区块；
计算所述至少两个图像区块中每一个图像区块的至少一个属性参数的参数值；
根据所述每一个图像区块的属性参数的参数值确定所述图像区块的属性参数的参数值；
根据所述图像的属性参数的参数值确定所述属性参数的评估值；根据所述属性参数的评估值确定所述图像的图像质量评估值。
在上述方案中，所述方法还包括：
将所述至少一个图像中的每一个图像的图像质量评估值与预设的评估值阈值进行比较；
将图像的图像质量评估值大于预设的评估值阈值的图像确定为满足预设的质量条件的图像。
在上述方案中，所述方法还包括：
当所述每一个图像的图像质量评估值不满足预设的质量条件时，将所述至少一个图像中的图像质量评估值最大的图像作为调整目标图像；
根据所述调整目标图像的至少一个属性参数的参数值调整所述调整目标图像的质量评估值。
在上述方案中，根据所述调整目标图像的至少一个属性参数的参数值调整所述调整目标图像的质量评估值包括：
获取所述调整目标图像的至少一个属性参数的参数值；
确定所述每一个属性参数的参数值对应的评估值，将属性参数的评估值中小于所述第一预设阈值的属性参数作为第一目标属性参数；
调整所述第一目标属性参数的参数值，直至所述第一目标属性参数的评估值大于或等于所述第一预设阈值。
在上述方案中，调整所述调整目标图像的质量评估值包括：
获取所述调整目标图像的至少一个属性参数的参数值；
确定所述每一个属性参数的参数值对应的评估值，将评估值小于第二预设阈值的属性参数作为第二目标属性参数；
对所述第二目标属性参数按照评估值大小进行排序；
对排序后的第二目标属性参数的参数值依次进行调整，直至所述调整目标图像的图像质量评估值大于或等于所述预设的评估值阈值。
在上述方案中，所述属性参数包括：锐度，对比度、饱和度、亮度和噪点
本公开实施例还一种拍照装置，所述装置包括：
采集模块，设置为获取针对同一图像采集区域采集的至少一个图像；
处理模块，设置为获取所述至少一个图像中的每一个图像的图像质量评估值，所述图像质量评估值用于表征所述每一个图像的质量；
确定模块，设置为将所述至少一个图像中所述图像质量评估值满足预设的质量条件的图像确定为目标图像，并生成拍照指令；
保存模块，设置为执行所述拍照指令，保存所述目标图像。
在上述方案中，所述装置，还包括：调整模块，设置为当所述每一个图像的图像质量评估值不满足预设的质量条件时，根据图像质量评估值对所述至少一个图像进行排序，将所述至少一个图像中的图像质量评估值最大的图像作为调整目标图像；根据所述调整目标图像的至少一个属性参数的参数值调整所述调整目标图像的质量评估值。
本公开实施例还提供了一种终端，包括：图像传感器、处理器和存储器；其中，
所述图像传感器，设置为获取针对同一图像采集区域采集的至少一个图像；
所述处理器，设置为获取所述至少一个图像中的每一个图像的图像质量评估值，所述图像质量评估值用于表征所述每一个图像的质量；将所述至少一个图像中所述图像质量评估值满足预设的质量条件的图像确定为目标图像，并生成拍照指令；执行所述拍照指令，将所述目标图像保存在所述存储器中。
本公开实施例还提供了一种存储介质，所述存储介质包括存储的程序，该程序运行时执行上述的拍照方法。
本公开实施例的拍照方法、装置、终端及存储介质，获取针对图像采集区域的图像，获取所述图像的图像质量评估值，所述图像质量评估值用于表征所述图像的质量；确定所述图像质量评估值满足预设的质量条件时， 生成拍照指令，执行所述拍照指令，将所述图像作为目标图像，保存所述目标图像，如此，将图像质量的评估值满足预设的质量条件的图像作为拍照的结果，另一方面，当针对图像采集区域的图像为多个图像时，将图像质量的评估值满足预设的质量条件的图像作为拍照的结果，实现了对目标场景的有效抓拍，进而保证了终端所拍摄的质量。
附图说明
此处所说明的附图用来提供对本公开的进一步理解，构成本公开的一部分，本公开的示意性实施例及其说明用于解释本公开，并不构成对本公开的不当限定。在附图中：
图1-1为本公开实施例一中的拍照方法的流程示意图；
图1-2为本公开实施例二中的拍照方法的流程示意图；
图2为本公开实施例三中的拍照方法的流程示意图；
图3为本公开实施例四中的拍照方法的流程示意图；
图4为本公开实施例四中的饱和度分析方法的流程示意图；
图5为本公开实施例五中的拍照装置的一种结构示意图；
图6为本公开实施例五中的拍照装置的另一种结构示意图；
图7为本公开实施例六中的终端的结构示意图。
具体实施方式
下面将结合本公开实施例中的附图，对本公开实施例中的技术方案进行清楚、完整地描述。
实施例一：
本公开可选实施例提供了一种拍照方法，本公开实施例拍照方法的执 行主体可以为拍照装置，该拍照装置可以内置或者外接于一终端。这里，终端可以为智能手机、平板电脑，数码相机等。
图1-1为本公开实施例一中的拍照方法的流程示意图，参见图1-1所示，该方法包括：
S1101、获取针对图像采集区域的图像，获取所述图像的图像质量评估值，所述图像质量评估值用于表征所述图像的质量；
这里，拍照的模式可为自动拍照模式，也可为手动拍照模式。对于自动拍照模式，当终端接收到自动拍照指令时，进入自动拍照模式，此时，通过摄像头采集图像采集区域的图像，这里，触发自动拍照指令或手动拍照指令的操作可通过语音操作/点选操作/触摸操作终端上的物理按键/虚拟按键的触发进入对应拍照模式。
当采集到图像采集区域的图像时，对该图像进行分析，获取图像的图像质量评估值，所述获取所述图像的图像质量评估值包括：获取所述图像的属性参数的参数值，根据所述属性参数的参数值确定所述图像的图像质量评估值；所述属性参数包括以下属性参数至少之一：锐度，对比度、饱和度、亮度和噪点。，获取图像的属性参数的方法可以采用特征提取方法，如：傅里叶变化、窗口傅里叶变化、小波变化、最小二乘法、边界方向直方图、基于Tzmura纹理特征的纹理特征提取等，当然，还可以有其它的算法，本公开实施例不做限定。
所述根据所述属性参数的参数值确定所述图像的图像质量评估值包括：将所述图像按照预设分区策略划分为至少两个图像区块；计算所述至少两个图像区块中每一个图像区块的属性参数的参数值；根据所述每一个图像区块的属性参数的参数值确定所述图像区块的属性参数的参数值；根据所述图像的属性参数的参数值确定所述属性参数的评估值；根据所述属性参数的评估值确定所述图像的图像质量评估值。
这里，确定图像区块的属性参数的参数值的一种可行的实现方式为：选取该图像区块的几何中心点，计算该图像区块的几何中心点的属性参数的参数值，并将该图像区块的几何中心处的属性参数的参数值作为该图像 区块的属性参数的参数值；图像的属性参数的参数值为所有图像区块的相同属性参数的取值范围，例如，以计算该图像的饱和度的参数值为例进行说明：选取该图像区块的几何中心点，计算该几何中心点的饱和度的参数值，将该几何中心点的饱和度值作为相应区块的饱和度的参数值，则该图像的饱和度的参数值为该图像中饱和度的取值范围。
其中，预设分区策略为默认的或用户自定义的根据预设的长和宽将图像划分为至少两个图像区块的策略。当将图像划分为至少两个图像区块并获取每个图像区块的属性参数的参数值后，确定图像的属性参数的参数值，根据图像的属性参数的参数值计算每一个图像的图像质量评估值。这里，根据图像的属性参数的参数值计算每一个图像的图像质量评估值的的方式可以且不限于以下一种实现方式为：根据预设的属性参数的参数值与评估值之间的映射关系，确定每一个图像的属性参数的评估值，根据所述属性参数的评估值确定所述图像的图像质量评估值。
这里，当每一个图像区块的属性参数为一个属性参数比如：饱和度时，则根据每一个图像区块的饱和度的值确定图像的饱和度的值，进一步的，将图像的饱和度的值对应的评估值确定为图像的图像质量评估值。当每一个图像区块的属性参数为多个属性参数比如：饱和度、对比度时，根据每一个图像区块的饱和度、对比度确定图像的饱和度、对比度，并分别根据饱和度、对比度的参数值确定饱和度、对比度对应的评估值，并通过预设的计算方式利用饱和度的评分制和对比度对应的评估值计算出图像质量评估值，这里，预设的计算方式可为计算各属性参数的评估值的算术平均值等计算方式，本公开实施例对此并不进行限定。
其中，图像的属性参数的参数值可能为一个区间值，根据预设的属性参数的参数值与属性参数的评估值之间的映射关系，查找图像的属性参数的参数值所属的映射区间，从而确定图像的属性参数的评估值；图像质量评估值的确定由该图像的至少一个属性参数的评估值的算术平均值来量化决定，例如，以饱和度和对比度为例，计算图像的图像质量评估值如下：根据预设的饱和度的参数值与饱和度的评估值之间的映射关系，得到每一个图像的饱和度的评估值；根据预设的对比度的参数值与对比度的评估值 之间的映射关系，得到每一个图像的对比度的评估值，计算每一个的饱和度的评估值和对比度的评估值的算术平均值，将该算术平均值作为相应图像的图像质量评估值。
S1102、确定所述图像质量评估值满足预设的质量条件时，生成拍照指令，执行所述拍照指令，将所述图像作为目标图像，保存所述目标图像。
这里，在确定所述图像质量评估值满足预设的质量条件之前，将所述图像的图像质量评估值与预设的评估值阈值进行比较；当所述图像的图像质量评估值大于预设的评估值阈值时，确定所述图像的图像质量评估值满足预设的质量条件。
这里，评估值阈值可以为系统默认设置的，也可以为用户在触发拍照过程中的任意时刻自定义设置的；用户预设评估值阈值的一种可行的实现方式为：通过屏幕提示用户设置触发自动拍照的图像质量评估值的阈值。
当所述图像的图像质量评估值不满足预设的质量条件时，根据所述属性参数的参数值对所述图像的图像质量评估值进行调整。
当确定图像质量评估值的属性参数为一个属性参数时，可直接对该属相参数的参数值进行调整，以使得图像质量评估值能够大于预设的评估值阈值，以对图像的图像质量进行调整，使得保存的目标图像为满足质量条件的图像。
当所述属性参数包括锐度，对比度、饱和度、亮度和噪点中的至少两个属性参数时，所述根据所述属性参数的参数值对所述图像的图像质量评估值进行调整包括：
确定所述每一个属性参数的参数值对应的评估值，根据所述评估值的大小对所述属性参数进行排序得到排序结果；根据所述排序结果调整各属相参数的参数值以对所述图像的图像质量评估值进行调整。
这里，当属性参数包括至少两个属性参数时，在调整的过程中，根据属性参数的评估值的大小对属性参数的参数值进行调整，比如：优先对评估值大的属性参数进行调整，以提高图像的整体的图像质量评估值。
在本公开实施例中，当进行拍照时，通过对图像的图像质量评估值的计算，来确定图像的质量是否满足质量条件，确定满足质量条件时，生成拍照指令进行图像的保存；当不符合质量条件时，对图像的质量进行调整，以保证保存的图像为满足质量条件的图像。进一步的，在计算图像的图像质量评估值时，将图像划分为多个图像区块，以根据各图像区块的属性参数的参数值确定图像的属相参数的参数值，进而确定出图像的图像质量评估值，以精确的计算出图像的图像质量评估值。
实施例二
本公开可选实施例提供了一种拍照方法，本公开可选实施例拍照方法的执行主体可以为拍照装置，该拍照装置可以内置或者外接于一终端。这里，终端可以为智能手机、平板电脑，数码相机等。
图1-2为本公开可选实施例二中的拍照方法的流程示意图，参见图1-2所示，该方法包括：
S101：获取针对同一图像采集区域采集的至少一个图像；
这里，当用户确定对准要拍摄的目标场景后，通过语音操作/点选操作/触摸操作终端上的物理按键/虚拟按键触发自动拍照模式请求时，终端通过图像传感器针对同一图像采集区域，采集至少一个图像；这里，采集的至少一个图像作为目标图像的选择图像进行缓存，并不作为最终保存的目标图像。在本实施例中，图像采集区域是指图像传感器的取景区域。采集图像的数量可以根据实际需要，由用户自定义设置，也可以由系统默认设置。当然，还可以存在其它设定方式，本公开实施例不做限定。
S102：获取所述至少一个图像中的每一个图像的图像质量评估值，图像质量评估值用于表征每一个图像的质量；
这里，终端需要对采集到的当前缓存的图像进行分析，得到每一个图像的图像质量评估值；
在实际应用中，图像的图像质量评估值可以为图像的至少一个属性参数的评估值的算术平均值；提取图像的属性参数的方法可以采用特征提取 方法，如：傅里叶变化、窗口傅里叶变化、小波变化、最小二乘法、边界方向直方图、基于Tzmura纹理特征的纹理特征提取等，当然，还可以有其它的算法，本公开实施例不做限定。
在实施过程中，为了获得一个图像的图像质量评估值，所述获取所述至少一个图像中的每一个图像的图像质量评估值，包括：获取所述每一个图像的至少一个属性参数的参数值；按照预设规则，根据每一个图像的至少一个属性参数的参数值，计算每一个图像的图像质量评估值。
这里，图像的属性参数可以为对比度、饱和度、亮度、锐度、噪声等，本公开实施例对此并不限定；这些属性参数的参数值可以作为衡量图像的图像质量的评价指标。
所述根据每一个图像的所述至少一个属性参数的参数值，计算每一个图像的图像质量评估值，包括：针对每一个图像，将所述图像按照预设分区策略划分为至少两个图像区块；计算所述至少两个图像区块中每一个图像区块的至少一个属性参数的参数值；根据所述每一个图像区块的属性参数的参数值确定所述图像区块的属性参数的参数值；根据所述图像的属性参数的参数值确定所述属性参数的评估值；根据所述属性参数的评估值确定所述图像的图像质量评估值。
这里，确定图像区块的属性参数的参数值的一种可行的实现方式为：选取该图像区块的几何中心点，计算该图像区块的几何中心点的属性参数的参数值，并将该图像区块的几何中心处的属性参数的参数值作为该图像区块的属性参数的参数值；图像的属性参数的参数值为所有图像区块的相同属性参数的取值范围，例如，以计算该图像的饱和度的参数值为例进行说明：选取该图像区块的几何中心点，计算该几何中心点的饱和度的参数值，将该几何中心点的饱和度值作为相应区块的饱和度的参数值，则该图像的饱和度的参数值为该图像中饱和度的取值范围。
预设分区策略为默认的或用户自定义的根据预设的长和宽将图像划分为至少两个图像区块。上述按照预设规则，根据至少一个属性参数的参数值，计算每一个图像的图像质量评估值的步骤可以且不限于以下一种实 现方式为：根据预设的属性参数的参数值与评估值之间的映射关系，确定每一个图像的至少一个属性参数的评估值，计算每一个图像的至少一个属性参数的评估值的算术平均值，将每一个图像的算术平均值作为相应图像的图像质量评估值。
由于图像的属性参数的参数值可能为一个区间值，根据预设的属性参数的参数值与属性参数的评估值之间的映射关系，查找图像的属性参数的参数值所属的映射区间，从而确定图像的属性参数的评估值；图像质量评估值的确定由该图像的至少一个属性参数的评估值的算术平均值来量化决定，例如，以饱和度和对比度为例，计算图像的图像质量评估值如下：根据预设的饱和度的参数值与饱和度的评估值之间的映射关系，得到每一个图像的饱和度的评估值；根据预设的对比度的参数值与对比度的评估值之间的映射关系，得到每一个图像的对比度的评估值，计算每一个的饱和度的评估值和对比度的评估值的算术平均值，将该算术平均值作为相应图像的图像质量评估值。
这里，获取的属性参数为一个属性参数时，可直接将图像的该属性参数的评估值作为图像的图像质量评估值。
S103：将至少一个图像中图像质量评估值满足预设的质量条件的图像确定为目标图像，并生成拍照指令；
这里，将所述至少一个图像中的每一个图像的图像质量评估值与预设的评估值阈值进行比较；将图像的图像质量评估值大于预设的评估值阈值的图像确定为满足预设的质量条件的图像。
计算出至少一个图像中当前缓存图像的图像质量评估值时，将该图像质量评估值与预设的评估值阈值进行比较，如何该图像质量评估值大于或等于预设的评估值阈值，确定该图像为目标图像。
这里，预设的评估值阈值可以为系统默认设置的，也可以为用户在触发拍照过程中的任意时刻自定义设置的；用户预设预设的评估值阈值的一种可行的实现方式为：通过屏幕提示用户设置触发自动拍照的图像质量评估值的阈值。
S104：执行拍照指令，保存目标图像。
将目标图像直接保存后，可以将目标图像通过终端的屏幕显示，这里，可删除图像质量评估值不满足预设的质量条件的图像。
需要说明的是，上述过程可以为：终端利用图像采集模块针对同一场景进行分别取景时，一次性采集至少一个图像后，对每一个图像进行处理；也可以为终端利用图像采集模块针对同一场景进行分别取景时，采集一个图像后，立即对该图像进行处理，直至i个图像质量满足预设拍摄所要求的质量条件而触发自动拍照，i为大于或等于1的正整数。
由此可见，本公开实施例通过针对同一图像采集区域，采集至少一个图像；首先，对至少一个图像中的每一个图像进行处理，获得每一个图像的图像质量评估值，图像质量评估值用于表征每一个图像的质量；能够在自动触发拍照前针对同一采集区域采集的图像进行图像质量评估，然后，将至少一个图像中图像质量评估值大于或等于预设的评估值阈值的图像确定为目标图像，并生成拍照指令；执行拍照指令，保存目标图像，并删除至少一个图像中图像质量评估值小于预设的评估值阈值的图像；可见，如果图像的图像质量评估值大于或等于自动触发拍照阈值，进行自动触发拍照，能够实现自动触发拍照，避免了不能及时抓拍目标景物，保证了所拍摄照片的质量。
实施例三：
本公开实施例提供了一种拍照方法，如图2所示，本公开实施例中针对至少一个图像中的每一个图像都不满足预设的质量条件的情况进行说明：
本公开实施例中至少一个图像中每一个图像的图像质量评估值小于预设的评估值阈值时，针对图像的属性参数的参数值进行的调整可以为对至少一个图像中的第k个图像的图像质量评估值进行的调整，也可以为对至少一个图像中的n个图像的图像质量评估值进行的调整；本公开实施例以对至少一个图像中的第k个图像的图像质量评估值进行的调整为例，进行说明：
S201：针对同一图像采集区域，采集至少一个图像；
S202：获取所述至少一个图像中的每一个图像的图像质量评估值，所述图像质量评估值用于表征所述每一个图像的质量；
S203：当所述每一个图像的图像质量评估值不满足预设的质量条件时，将所述至少一个图像中的图像质量评估值最大的图像作为调整目标图像，根据所述调整目标图像的至少一个属性参数的参数值调整所述调整目标图像的质量评估值；
对质量评估值的调整可以通过调整影响图像质量的属性参数，调整方法可以采用线性校正和非线性校正。
在实施过程中，为了调整至少一个图像中的调整目标图像的图像质量评估值，S203的可行的实现方式可以以下列两种方式实施：
方式1、获取调整目标图像的至少一个属性参数的参数值；确定所述每一个属性参数的参数值对应的评估值，将属性参数的评估值中小于第一预设阈值的属性参数作为第一目标属性参数；调整第一目标属性参数的参数值，直至第一目标属性参数的评估值大于或等于第一预设阈值。
这里，第一预设阈值的取值可以与预设的评估值阈值的取值相同，也可以与预设的评估值阈值的取值不同，本公开实施例对此并不限定；调整第一目标属性参数的参数值可以为将第一目标属性参数中每一个属性参数的参数值进行调整，例如，对调整目标图像进行处理，分别获得调整目标图像的对比度的参数值为(a，b)，亮度的参数值为(c，d)，饱和度的参数值为(e，f)；根据预设的对比度的参数值与评估值之间的映射关系，可得到对比度的评估值为60；根据预设的亮度的参数值与评估值之间的映射关系，可得到亮度的评估值为70；根据预设的饱和度的参数值与评估值之间的映射关系，可得到饱和度的评估值为80；由于第一预设阈值为75，则小于75的属性参数为对比度和亮度，分别调整对比度和亮度的参数值，直至对比度和亮度的评估值大于或等于75。
方式2、获获取所述调整目标图像的至少一个属性参数的参数值；
确定所述每一个属性参数的参数值对应的评估值，将评估值小于第二预设阈值的属性参数作为第二目标属性参数；对第二目标属性参数按照评估值大小进行排序；将排序后的第二目标属性参数的参数值进行依次调整，直至调整目标图像的图像质量评估值大于或等于预设的评估值阈值。
其中，第一预设阈值的大小可与第二预设阈值的大小相同，也可不同。
这里，将第二目标属性参数按照评估值的大小进行排序，例如，可以为按照评估值由小到大的顺序，本公开实施例对此并不限定。这里，当设置的第二预设阈值大于属性参数最大的评估值时，则第二目标属性参数包括所有的属性参数。将所有的属性参数的评估值进行排序。
上述将调整后的第二目标属性参数的参数值依次进行调整的步骤可以且不限定于以下一种实现方式：先调整第二目标属性参数中的第一个属性参数，计算调整后的调整目标图像的图像质量评估值，如果调整后的调整目标图像的图像质量评估值大于或等于预设的评估值阈值，则保存调整目标图像；如果调整后的调整目标图像的图像质量评估值小于预设的评估值阈值，则调整第二个属性参数，直至第k个图像的图像质量评估值大于预设的评估值阈值，例如，对调整目标图像进行处理，分别获得调整目标图像的对比度的参数值为(a，b)，亮度的参数值为(c，d)，饱和度的参数值为(e，f)；根据预设的对比度的参数值与评估值之间的映射关系，可得到对比度的评估值为60；根据预设的亮度的参数值与评估值之间的映射关系，可得到亮度的评估值为70；根据预设的饱和度的参数值与评估值之间的映射关系，可得到饱和度的评估值为80；由于第二预设阈值为75，则小于75的属性参数为对比度和亮度，由于对比度的评估值小于亮度的评估值，首先调整对比度的参数值，直至对比度的评估值为75，然后判断调整后的对比度的评估值、亮度的评估值和饱和度的评估值的算术平均值是否大于或者等于预设的评估值阈值75，由于调整后的算术平均值等于预设的评估值阈值，因此不再调整亮度的参数值。
S204：将至少一个图像中图像质量评估值满足预设的质量条件的图像确定为目标图像，并生成拍照指令；
这里，满足预设的质量条件的图像为调整后的调整目标图像
S205：执行拍照指令，保存目标图像。
本公开实施例中，终端通过当前预览图片的属性参数进行调整，使得当前预览图像的图像质量评估值满足预设的质量条件，然后，将调整后的当前预览图像保存，实现了自动拍照，并保证了所拍摄照片的质量。
实施例四：
本公开实施例提供了一种拍照方法，如图3所示，对本公开实施例的实现流程详细说明：
S301：进入相机应用的预览界面；
S302：提示用户是否需要打开自动拍照功能；
S303：如果用户选择开启自动拍照功能，则提示用户输入自动触发拍照的预设的评估值阈值；
这里，若用户没有输入上述阈值时，则采用默认阈值。此时，假设拍照触发的阈值为90分。
S304：计算当前预览图片进行属性参数的参数值；
这里，图像质量分析包括以下几方面：1、饱和度分析；2、噪声分析；3、锐度分析；4、对比度分析；5、亮度分析。当然，还可以为其它参数的分析，本公开实施例不做限定。
下面以饱和度分析为例进行详细说明，参见图4所示，假定当前预览图片的宽和高分别为W、H。将该预览图片划分为a1，a2，……a(N-1)，aN，共N个区块，N为大于或者等于1的整数。
首先，选取N个区块中第i个区块的中心点，根据饱和度计算公式(1)，获得该区块中心点的饱和度Si；
S＝(MaxV-MinV)/MaxV      (1)
其中，S为区块中心点的饱和度，区块中心点的明度最大值MaxV＝max(R,G,B)，区块中心点的明度最小值MinV＝min(R,G,B)；R为区块中心点的红色通道的取值，G为区块中心点的绿色通道的取值，B为区块中心点的蓝色通道的取值。
第二步，依次计算出S1，S2，……SN；
第三步，根据下述公式(2)和公式(3)，获得当前预览图片的饱和度取值范围为(Smin，Smax)；
Smin＝min(S1，S2，……SN)     (2)
Smax＝max(S1，S2，……SN)     (3)
第四步，将饱和度取值范围为(Smin，Smax)作为饱和度的参数值。
同理，参照上述方法，终端还可以获得噪声的参数值、锐度的参数值、对比度的参数值以及亮度的参数值。
S305：计算当前预览图片的属性参数的评估值；
下面以当前预览图片的饱和度的评估值为例说明.
首先，根据预设的饱和度的参数值与饱和度的评估值之间的映射关系，获得S304中获得的饱和度的参数值(Smin，Smax)的评估值S_saturation。例如，假设(Smin，Smax)在85％-95％之间，那么，根据上述映射关系，可以得到饱和度的评估值为95分。
同理，参照上述方法，终端还可以根据预设的属性参数的参数值与属性参数的评估值之间的映射关系，获得当前预览图片的对比度的评估值S_contrast、亮度的评估值S_luminance、锐度的评估值S_sharpness以及噪声的评估值S_noise等方面的评估值；
S306：根据S_saturation、S_contrast、S_luminance、S_sharpness以及S_noise，计算当前预览图片的图像质量评估值Score；
这里，终端可以根据下述公式(4)来计算当前预览图片的图像质量评估值。
Score＝(S_saturation+S_noise+S_sharpness+S_contrast+S_luminance)/5  (4)
S307：比较Score与S_threshold的大小，当Score大于或者等于S_threshold时，执行S313；当Score小于S_threshold时，执行S308；
这里，S_threshold为触发拍照的阈值。
S308：从S_saturation、S_contrast、S_luminance、S_sharpness以及S_noise中筛选出小于S_threshold的属性参数；
S309：将小于S_threshold的属性参数按照从大到小的顺序进行排序；
S310：将第i个属性参数调整至S_threshold后，执行S311；
这里，i的初始取值为5。
S311：基于调整后的属性参数的参数值，计算当前预览图像的图像质量评估值Score_mod；
S312：如果Score_mod大于或者等于S_threshold时，执行S313；如果Score_mod小于S_threshold时，i＝i-1，返回S311；
S313：保存调整后的当前预览图像。
实施例五：
基于同一公开构思，本实施例提供一种拍照装置，该拍照装置可以应用于上述一个或者多个实施例中所述的终端。
图5为本公开可选实施例中的拍照装置的结构示意图，如图5所示，该拍照装置50，包括：采集模块51，设置为获取针对同一图像采集区域采集的至少一个图像；处理模块52，设置为获取所述至少一个图像中的每一个图像的图像质量评估值，图像质量评估值用于表征每一个图像的质量；确定模块53，设置为将至少一个图像中图像质量评估值满足预设的质量条件的图像确定为目标图像，并生成拍照指令；保存模块54，设置为执行拍照指令，保存目标图像。
在本公开其它实施例中，处理模块52，获取所述至少一个图像中的每 一个图像的图像质量评估值，包括：获取每一个图像的至少一个属性参数的参数值；按照预设规则，根据每一个图像的至少一个属性参数的参数值，计算每一个图像的图像质量评估值。
在本公开其它实施例中，处理模块52，根据每一个图像的所述至少一个属性参数的参数值，计算每一个图像的图像质量评估值包括：针对每一个图像，将所述图像按照预设分区策略划分为至少两个图像区块；计算所述至少两个图像区块中每一个图像区块的至少一个属性参数的参数值；根据所述每一个图像区块的属性参数的参数值确定所述图像区块的属性参数的参数值；根据所述图像的属性参数的参数值确定所述属性参数的评估值；根据所述属性参数的评估值确定所述图像的图像质量评估值。。
在本公开其它实施例中，如图6所示，拍照装置50，还可以包括：比较模块55，设置为将所述至少一个图像中的每一个图像的图像质量评估值与预设的评估值阈值进行比较；将图像的图像质量评估值大于预设的评估值阈值的图像确定为满足预设的质量条件的图像。
在本公开其它实施例中，如图6所示，拍照装置，还可以包括：调整模块56，设置为如果每一个图像的图像质量评估值不满足预设的质量条件时，将所述至少一个图像中的图像质量评估值最大的图像作为调整目标图像；根据所述调整目标图像的至少一个属性参数的参数值调整所述调整目标图像的质量评估值。
在实际应用中，采集模块、处理模块、确定模块、保存模块、比较模块和调整模块均可由位于拍照装置的中央处理器(CPU，Central Processing Unit)、微处理器(MPU，Microprocessor Unit)、数字信号处理器(DSP，Digital Signal Processing)、或现场可编程门阵列(FPGA，Field－Programmable Gate Array)等实现。本公开实施例不做限定。
这里需要指出的是：以上装置实施例项的描述，与上述方法描述是类似的，具有同方法实施例相同的有益效果，因此不做赘述。对于本公开装置实施例中未披露的技术细节，本领域的技术人员请参照本公开方法实施例的描述而理解，为节约篇幅，这里不再赘述。
实施例六：
基于同一公开构思，本公开实施例提供一种终端，该终端与上述一个或者多个实施例中所述的终端一致。
参见图7所示，该终端70，包括：图像传感器71、处理器72和存储器73，其中，图像传感器71，所述图像传感器，设置为获取针对同一图像采集区域采集的至少一个图像；处理器72，设置为获取所述至少一个图像中的每一个图像的图像质量评估值，所述图像质量评估值用于表征所述每一个图像的质量；将所述至少一个图像中所述图像质量评估值满足预设的质量条件的图像确定为目标图像，并生成拍照指令；执行所述拍照指令，将所述目标图像保存在存储器73中。
这里，上述处理器可以由CPU、MPU、DSP或FPGA等实现。本公开实施例不做限定。
实施例七：
基于同一公开构思，本公开实施例提供一种存储介质，可选地，在本实施例中，上述存储介质可以被设置为存储用于执行以下步骤的程序代码：
S1，获取针对图像采集区域的图像，获取图像的图像质量评估值，图像质量评估值用于表征图像的质量；
S2，确定图像质量评估值满足预设的质量条件时，生成拍照指令，执行拍照指令，将图像作为目标图像，保存目标图像。
可选地，存储介质还被设置为存储用于执行以下步骤的程序代码：
S1，获取针对同一图像采集区域采集的至少一个图像；
S2，获取至少一个图像中的每一个图像的图像质量评估值，图像质量评估值用于表征每一个图像的质量；
S3，将至少一个图像中图像质量评估值满足预设的质量条件的图像确定为目标图像，并生成拍照指令；
S4，执行拍照指令，保存目标图像。
这里需要指出的是：以上终端实施例项的描述，与上述方法描述是类似的，具有同方法实施例相同的有益效果，因此不做赘述。对于本公开终端实施例中未披露的技术细节，本领域的技术人员请参照本公开方法实施例的描述而理解，为节约篇幅，这里不再赘述。
本领域内的技术人员应明白，本公开的实施例可提供为方法、系统、或计算机程序产品。因此，本公开可采用硬件实施例、软件实施例、或结合软件和硬件方面的实施例的形式。而且，本公开可采用在一个或多个其中包含有计算机可用程序代码的计算机可用存储介质(包括但不限于磁盘存储器和光学存储器等)上实施的计算机程序产品的形式。
本公开是参照根据本公开实施例的方法、设备(系统)、和计算机程序产品的流程图和/或方框图来描述的。应理解可由计算机程序指令实现流程图和/或方框图中的每一流程和/或方框、以及流程图和/或方框图中的流程和/或方框的结合。可提供这些计算机程序指令到通用计算机、专用计算机、嵌入式处理机或其他可编程数据处理设备的处理器以产生一个机器，使得通过计算机或其他可编程数据处理设备的处理器执行的指令产生用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的装置。
这些计算机程序指令也可存储在能引导计算机或其他可编程数据处理设备以特定方式工作的计算机可读存储器中，使得存储在该计算机可读存储器中的指令产生包括指令装置的制造品，该指令装置实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能。
这些计算机程序指令也可装载到计算机或其他可编程数据处理设备上，使得在计算机或其他可编程设备上执行一系列操作步骤以产生计算机实现的处理，从而在计算机或其他可编程设备上执行的指令提供用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的 功能的步骤。
以上，仅为本公开的较佳实施例而已，并非用于限定本公开的保护范围。
工业实用性
通过本公开的技术方案，获取针对图像采集区域的图像，获取所述图像的图像质量评估值，所述图像质量评估值用于表征所述图像的质量；确定所述图像质量评估值满足预设的质量条件时，生成拍照指令，执行所述拍照指令，将所述图像作为目标图像，保存所述目标图像，如此，将图像质量的评估值满足预设的质量条件的图像作为拍照的结果，另一方面，当针对图像采集区域的图像为多个图像时，将图像质量的评估值满足预设的质量条件的图像作为拍照的结果，实现了对目标场景的有效抓拍，进而保证了终端所拍摄的质量。

Claims (18)

  1. 一种拍照方法，所述方法包括：
    获取针对图像采集区域的图像，获取所述图像的图像质量评估值，所述图像质量评估值用于表征所述图像的质量；
    确定所述图像质量评估值满足预设的质量条件时，生成拍照指令，执行所述拍照指令，将所述图像作为目标图像，保存所述目标图像。
  2. 根据权利要求1所述的方法，其中，所述获取所述图像的图像质量评估值包括：
    获取所述图像的属性参数的参数值，根据所述属性参数的参数值确定所述图像的图像质量评估值；
    所述属性参数包括以下属性参数至少之一：锐度，对比度、饱和度、亮度和噪点。
  3. 根据权利要求2所述的方法，其中，所述根据所述属性参数的参数值确定所述图像的图像质量评估值包括：
    将所述图像按照预设分区策略划分为至少两个图像区块；
    计算所述至少两个图像区块中每一个图像区块的属性参数的参数值；
    根据所述每一个图像区块的属性参数的参数值确定所述图像区块的属性参数的参数值；
    根据所述图像的属性参数的参数值确定所述属性参数的评估值；根据所述属性参数的评估值确定所述图像的图像质量评估值。
  4. 根据权利要求2所述的方法，其中，所述方法还包括：
    将所述图像的图像质量评估值与预设的评估值阈值进行比较；
    当所述图像的图像质量评估值大于预设的评估值阈值时，确定所述图像的图像质量评估值满足预设的质量条件。
  5. 根据权利要求2所述的方法，其中，所述方法还包括：
    当所述图像的图像质量评估值不满足预设的质量条件时，根据所述属性参数的参数值对所述图像的图像质量评估值进行调整。
  6. 根据权利要求5所述的方法，其中，当所述属性参数包括锐度，对比度、饱和度、亮度和噪点中的至少两个属性参数时，所述根据所述属性参数的参数值对所述图像的图像质量评估值进行调整包括：
    确定所述每一个属性参数的参数值对应的评估值，根据所述评估值的大小对所述属性参数进行排序得到排序结果；
    根据所述排序结果调整各属相参数的参数值以对所述图像的图像质量评估值进行调整。
  7. 一种拍照方法，所述方法包括：
    获取针对同一图像采集区域采集的至少一个图像；
    获取所述至少一个图像中的每一个图像的图像质量评估值，所述图像质量评估值用于表征所述每一个图像的质量；
    将所述至少一个图像中所述图像质量评估值满足预设的质量条件的图像确定为目标图像，并生成拍照指令；
    执行所述拍照指令，保存所述目标图像。
  8. 根据权利要求7所述的方法，其中，所述获取所述至少一个 图像中的每一个图像的图像质量评估值，包括：
    获取所述每一个图像的至少一个属性参数的参数值；
    按照预设规则，根据每一个图像的所述至少一个属性参数的参数值，计算每一个图像的图像质量评估值。
  9. 根据权利要求8所述的方法，其中，所述根据每一个图像的所述至少一个属性参数的参数值，计算每一个图像的图像质量评估值，包括：
    针对每一个图像，将所述图像按照预设分区策略划分为至少两个图像区块；
    计算所述至少两个图像区块中每一个图像区块的至少一个属性参数的参数值；
    根据所述每一个图像区块的属性参数的参数值确定所述图像区块的属性参数的参数值；
    根据所述图像的属性参数的参数值确定所述属性参数的评估值；根据所述属性参数的评估值确定所述图像的图像质量评估值。
  10. 根据权利要求8所述的方法，其中，所述方法还包括：
    将所述至少一个图像中的每一个图像的图像质量评估值与预设的评估值阈值进行比较；
    将图像的图像质量评估值大于预设的评估值阈值的图像确定为满足预设的质量条件的图像。
  11. 根据权利要求8所述的方法，其中，所述方法还包括：
    当所述每一个图像的图像质量评估值不满足预设的质量条件时， 将所述至少一个图像中的图像质量评估值最大的图像作为调整目标图像；
    根据所述调整目标图像的至少一个属性参数的参数值调整所述调整目标图像的质量评估值。
  12. 根据权利要求11所述的方法，其中，根据所述调整目标图像的至少一个属性参数的参数值调整所述调整目标图像的质量评估值包括：
    获取所述调整目标图像的至少一个属性参数的参数值；
    确定所述每一个属性参数的参数值对应的评估值，将属性参数的评估值中小于所述第一预设阈值的属性参数作为第一目标属性参数；
    调整所述第一目标属性参数的参数值，直至所述第一目标属性参数的评估值大于或等于所述第一预设阈值。
  13. 根据权利要求11所述的方法，其中，调整所述调整目标图像的质量评估值包括：
    获取所述调整目标图像的至少一个属性参数的参数值；
    确定所述每一个属性参数的参数值对应的评估值，将评估值小于第二预设阈值的属性参数作为第二目标属性参数；
    对所述第二目标属性参数按照评估值大小进行排序；
    对排序后的第二目标属性参数的参数值依次进行调整，直至所述调整目标图像的图像质量评估值大于或等于所述预设的评估值阈值。
  14. 根据权利要求8所述的方法，其中，所述属性参数包括：锐 度，对比度、饱和度、亮度和噪点
  15. 一种拍照装置，所述装置包括：
    采集模块，设置为获取针对同一图像采集区域采集的至少一个图像；
    处理模块，设置为获取所述至少一个图像中的每一个图像的图像质量评估值，所述图像质量评估值用于表征所述每一个图像的质量；
    确定模块，设置为将所述至少一个图像中所述图像质量评估值满足预设的质量条件的图像确定为目标图像，并生成拍照指令；
    保存模块，设置为执行所述拍照指令，保存所述目标图像。
  16. 根据权利要求15所述的装置，其中，所述装置，还包括：调整模块，设置为当所述每一个图像的图像质量评估值不满足预设的质量条件时，根据图像质量评估值对所述至少一个图像进行排序，将所述至少一个图像中的图像质量评估值最大的图像作为调整目标图像；根据所述调整目标图像的至少一个属性参数的参数值调整所述调整目标图像的质量评估值。
  17. 一种终端，包括：图像传感器、处理器和存储器；其中，
    所述图像传感器，设置为获取针对同一图像采集区域采集的至少一个图像；
    所述处理器，设置为获取所述至少一个图像中的每一个图像的图像质量评估值，所述图像质量评估值用于表征所述每一个图像的质量；将所述至少一个图像中所述图像质量评估值满足预设的质量条件的图像确定为目标图像，并生成拍照指令；执行所述拍照指令，将所述目标图像保存在所述存储器中。
  18. 一种存储介质，所述存储介质包括存储的程序，其中，所述程序运行时执行上述权利要求1至14任一项中所述的方法。
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